SciTec has immediate opportunities for talented software and algorithm developers to support our radar modernization programs, which focus on ultra-low-latency signal processing, data fusion, and advanced tracking algorithms for upgraded ground-based radar systems. Ideal candidates will be comfortable working across multiple programming languages in a fast-paced, collaborative environment composed of scientists, engineers, and developers. You will rapidly prototype advanced radar algorithms and help transition them into optimized C++ implementations running on Linux within government frameworks. Your work will directly contribute to modernizing legacy radar systems with digital architectures, scalable processing pipelines, and mission-ready performance.
Responsibilities- Lead the research, development, and maturation of advanced numerical algorithms for radar signal and data exploitation, including detection, tracking, estimation, clutter suppression, and processing for modernized radar architectures.
- Design, implement, and optimize high-performance radar tracking algorithms in Python and C++, with emphasis on scalability, latency reduction, and robustness for operational radar missions.
- Develop and tune Kalman filtering, tracking, and data exploitation algorithms in Python and C++
- Develop and optimize Resource Management algorithms based on mission requirements
- Architect and develop end-to-end radar processing pipelines, from raw I/Q ingest through DSP chains, feature extraction, tracking, and production deployment in mission environments.
- Advance radar modeling, simulation, and algorithm-evaluation toolchains, including reusable frameworks that support rapid prototyping, validation, and integration of new radar capabilities.
- Define and execute quantitative radar-performance assessments including detection metrics, tracking accuracy, false-alarm characterization, sensitivity studies, and validation using real radar data.
- Collaborate cross-functionally with software engineers, system architects, RF engineers, and mission stakeholders to integrate algorithms into operational radar systems and ensure mission alignment.
- Provide technical leadership within Agile development teams, mentor junior engineers, drive radar-focused best practices, and contribute to shared DSP and algorithm codebases.
- Support proposal efforts, technical roadmaps, and customer engagements by clearly articulating radar algorithmic approaches, performance advantages, and modernization benefits.
- Ensure compliance with mission assurance, cybersecurity, and software-quality standards relevant to DoD radar programs.
- Other duties as assigned.
Requirements- Bachelor's or Master's degree in Applied Mathematics, Physics, Electrical Engineering, Computer Science, or related technical field
- 8+ years of experience developing numerical algorithms for radar signal processing or related sensor-processing applications
- Demonstrated expertise in developing and implementing algorithms in Python and C++
- Strong foundation in numerical methods, linear algebra, probability/statistics, and optimization techniques
- Experience working with real radar data (e.g., I/Q samples, pulse-compressed data, tracking data, or radar simulations)
- Proven ability to evaluate algorithm performance, including error analysis, validation, and benchmarking
- Experience working in Linux-based development environments and modern software development practices (version control, testing, CI/CD)
- Ability to work effectively in Agile or iterative development environments
- Strong written and verbal communication skills, including ability to convey complex technical concepts to diverse stakeholders
- U.S. Citizenship with ability to obtain and maintain a DoD security clearance (active clearance preferred)
Candidates who have any of the following skills will be preferred
- PhD in Applied Mathematics, Physics, Electrical Engineering, or related technical field
- Experience with advanced radar DSP techniques (e.g., CFAR, MTI/MTD, beamforming, calibration, Doppler processing, tracking filters, estimation algorithms, inverse problems)
- Familiarity with machine-learning methods applied to radar data (e.g., classification, anomaly detection, deep learning-based radar feature extraction)
- Experience optimizing radar algorithms for performance (parallel computing, GPU acceleration, vectorization, memory optimization)
- Knowledge of DoD radar mission systems, radar phenomenology, or ground-/air-based radar architectures
- Experience transitioning radar algorithms from prototype to production in operational radar environments
- Familiarity with containerization and orchestration tools (Docker, Kubernetes)
- Experience with radar modeling and simulation environments supporting system development
- Prior experience leading technical efforts or mentoring junior engineers
- Active DoD security clearance
*Resumes, Cover Letters, and Applications which are generated by AI will not be considered for employmentColorado Residents: In any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.BenefitsSciTec offers a highly competitive salary and benefits package, including:
- 4% Safe Harbor 401(k) match
- 100% company paid HSA Medical insurance, with a choice of 2 buy-up options
- 80% company paid Dental insurance
- 100% company paid Vision insurance
- 100% company paid Life insurance
- 100% company paid Long-term Disability insurance
- 100% company paid Hospital Indemnity insurance
- Voluntary Accident and Critical Illness insurance
- Short-term Disability insurance
- Annual Profit-Sharing Plan
- Discretionary Performance Bonus
- Paid Parental Leave
- Generous Paid Time Off, including Holiday, Vacation, and Sick Pay
- Flexible Work Hours
The pay range for this position is $156,000 - $193,000 / year. SciTec considers several factors when extending an offer of employment, including but not limited to the role and associated responsibilities, a candidate's work experience, education/training, and key skills. This is not a guarantee of compensation.
